Networked Life

Michael Kearns

Networked Life will explore recent scientific efforts to explain social, economic and technological structures — and the way these structures interact — on many different scales, from the behavior of individuals or small groups to that of complex networks such as the Internet and the global economy.

Announcements

Certificates Released; Thoughts and Comments on the Course

All, I have now determined grading criteria and created and released course certificates. As promised in an earlier announcement, grading was done as follows: every quiz was normalized to be equally weighted, regardless of the number of questions. So each quiz was calibrated to give a score between 0 and 100%. Your four lowest quiz scores were dropped, and your overall score was the average of the remaining quizzes.

I set the threshold for receiving a certificate to be an average of 65% after dropping your four lowest quizzes. While there will always be a somewhat arbitrary aspect to setting any hard threshold, I determined this value after looking at some raw student scores. The threshold used seemed to have the desirable property of awarding a certificate to almost all students who had attempted all or nearly all quizzes, and had done reasonably well on them. I tried to be somewhat lenient in both the threshold and the dropping of four scores to account for some bugs and glitches in the early quizzes. I also decided to award certificates with Distinction to the small group of students whose average was 100%.

I am told by Coursera staff that certificates are not emailed to you directly; rather, there is an area on the Coursera platform where you should be able to go and view all certificates you have received.

Finally, some closing personal remarks and observations on the course.

First of all, I want to thank you all for making this a tremendously rewarding experience for me as an educator. I spent much of my summer designing, recording and producing the videos, and will admit it took much more effort than I anticipated (despite already expecting it to be quite a bit going in). There was definitely a period in August when I was somewhat exhausted by the work it seemed to take to produce even small amounts of quality video, and wondered whether it would be worth it in the end. But the incredible diversity of the students in this first offering, your enthusiasm for the material, and your optimism about online education have made me proud to have done this, and thankful that I didn't give up or reduce my goals when it was hardest.

As you will have seen from the discussion forums, you are a tremendously diverse group, in every sense --- geographic, ethnic, professional, etc. I was particularly surprised and pleased to see how many working professionals there were taking the course, as well as graduate students of various kinds whose intellectual interests overlapped with course themes.

In terms of future courses --- I don't yet have concrete plans to offer a more advanced or follow-up to Networked Life, but I am favorably inclined to do so at some point, or perhaps offer a more advanced course on other topics that are part of my research, such as computational learning theory or algorithmic trading. But I do plan to offer Networked Life again, hopefully early in the new year. Among the things I hope to do to improve the course before then are:

* Improve the quality of the quizzes* Add a midterm and a final* Add a few lectures on additional topics* Add a more formal student survey on background, interests, and ideas for course improvement

Once again, thanks to all of you; it was a real pleasure. While I refrained from responding frequently to the forums during the course just due to time constraints, if someone wants to start a "Q&A with the prof" thread in the forums, I'd be happy to monitor it over the coming week or so and answer some (probably not all:)) of your questions.

Computing for Data Analysis

Roger D. Peng

This course is about learning the fundamental computing skills necessary for effective data analysis. You will learn to program in R and to use R for reading data, writing functions, making informative graphs, and applying modern statistical methods.

Announcements

Thank Your for Participating in Computing for Data Analysis!

I wanted to take this opportunity to thank everyone for participating in the inaugural offering of Computing for Data Analysis. As this was my first time running one of these courses, there were a number of bumps along the way. However, I appreciate everyone working with me and with each other to help smooth the ride. I was tremendously impressed by the activity on the discussion forums and the manner in which you helped your fellow students out with the quizzes and the programming assignments.

My goal for everyone in this class was to give you a start on using R and figuring out how it works. At this point, you should feel comfortable executing basic operations with data in R, executing simple data analyses from the command line, writing R functions, and making plots of data using the base and the lattice graphics system. From the beginning, I didn't think it was possible to turn everyone into an expert over a mere four weeks, however I wanted to get everyone at least to a place where they could continue to learn more on their own if they were so motivated.

I regret that it was also impossible to teach everyone statistics at the same time we were covering R and so the ultimate use of the R language, for doing statistical analyses, was not well-covered. However, my colleague Jeff Leek will be teaching the course Data Analysis through Coursera starting this January 22nd. I hope some of you will enroll in that class and take with you some of the R skills that you have learned here.

I the coming days I will be calculating the final grades and sending out the certificates of completion. Thank you all again for participating in the course.